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Quantum++ - A C++11 quantum computing library

Vlad Gheorghiu

Published Dec 15, 2014• 6 citations
OpenAlex

Abstract

Quantum++ is a modern general-purpose multi-threaded quantum computing library and simulator written in C++11 and composed solely of header files. The library is not restricted to qubit systems or specific quantum information processing tasks, being capable of simulating arbitrary quantum processes. The main design factors taken in consideration were the ease of use, portability, and performance.

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Quantum++ is a modern general-purpose multi-threaded quantum computing library and simulator written in C++11 and composed solely of header files. The library is not restricted to qubit systems or specific quantum information processing tasks, being capable of simulating arbitrary quantum processes. The main design factors taken in consideration were the ease of use, portability, and performance.
Quantum++ is a modern general-purpose multi-threaded quantum computing library written in C++11 and composed solely of header files. The library is not restricted to qubit systems or specific quantum information processing tasks, being capable of simulating arbitrary quantum processes. The main design factors taken in consideration were the ease of use, portability, and performance. The library's simulation capabilities are only restricted by the amount of available physical memory. On a typical machine (Intel i5 8Gb RAM) Quantum++ can successfully simulate the evolution of 25 qubits in a pure state or of 12 qubits in a mixed state reasonably fast. The library also includes support for classical reversible logic, being able to simulate classical reversible operations on billions of bits. This latter feature may be useful in testing quantum circuits composed solely of Toffoli gates, such as certain arithmetic circuits.
We introduce qclab++, a light-weight, fully-templated C++ package for GPU-accelerated quantum circuit simulations. The code offers a high degree of portability as it has no external dependencies and the GPU kernels are generated through OpenMP offloading. qclab++ is designed for performance and numerical stability through highly optimized gate simulation algorithms for 1-qubit, controlled 1-qubit, and 2-qubit gates. Furthermore, we also introduce qclab, a quantum circuit toolbox for Matlab with a syntax that mimics qclab++. This provides users the flexibility and ease of use of a scripting language like Matlab for studying their quantum algorithms, while offering high-performance GPU acceleration when required. As such, the qclab++ library offers a unique combination of features. We compare the CPU simulator in qclab++ with the GPU kernels generated by OpenMP and observe a speedup of over 40×40\times40×. Furthermore, we also compare qclab++ to other circuit simulation packages, such as cirq-qsim and qibo, in a series of benchmarks conducted on NERSC's Perlmutter system and illustrate its competitiveness.
Quantum circuit simulators have a long tradition of exploiting massive hardware parallelism. Most of the times, parallelism has been supported by special purpose libraries tailored specifically for the quantum circuits. Quantum circuit simulators are integral part of quantum software stacks, which are mostly written in Python. Our focus has been on ease of use, implementation and maintainability within the Python ecosystem. We report the performance gains we obtained by using CuPy, a general purpose library (linear algebra) developed specifically for CUDA-based GPUs, to simulate quantum circuits. For supremacy circuits the speedup is around 2x, and for quantum multipliers almost 22x compared to state-of-the-art C++-based simulators.
Quantum computing is a promising approach of computation that is based on equations from Quantum Mechanics and nanotechnology. Understanding and simulating quantum operations on a classical computer has different approaches and is modeled in different ways. However, the most repute ways are Quantum Turing Machine, Network Model or circuit model of connected gates and Quantum Programming Language. Many simulators do exist that varies in many features such as implementation languages, target platforms, paradigms, visuality, and applied quantum algorithms. There was a developmental trade-off between the simplicity and the functionality of the simulator. The goals and research activities are outlined as follows: First, surveying the quantum computing world, its characteristics, issues, problems, and challenges. Second, surveying the existing quantum simulators, illustrating representative simulators of major approaches, their features, and functionalities. Third, introducing a framework to provide the power of quantum computing , while insisting the simplicity and high usability. Finally, providing a case study for a new quantum algorithm based on the introduced framework.
We introduce the Simulator for Quantum Networks and Channels (SQUANCH\texttt{SQUANCH}SQUANCH), an open-source Python library for creating parallelized simulations of distributed quantum information processing. The framework includes many features of a general-purpose quantum computing simulator, but it is optimized specifically for simulating quantum networks. It includes functionality to allow users to easily design complex multi-party quantum networks, extensible classes for modeling noisy quantum channels, and a multiprocessed NumPy backend for performant simulations. We present an overview of the structure of the library, describing how the various API elements represent the underlying physics and providing simple usage examples for each module. Finally, we present several demonstrations of canonical quantum information protocols implemented using this framework.
We introduce QCLAB, an object-oriented MATLAB toolbox for constructing, representing, and simulating quantum circuits. Designed with an emphasis on numerical stability, efficiency, and performance, QCLAB provides a reliable platform for prototyping and testing quantum algorithms. For advanced performance needs, QCLAB++ serves as a complementary C++ package optimized for GPU-accelerated quantum circuit simulations. Together, QCLAB and QCLAB++ form a comprehensive toolkit, balancing the simplicity of MATLAB scripting with the computational power of GPU acceleration. This paper serves as an introduction to the package and its features along with a hands-on tutorial that invites researchers to explore its capabilities right away.